In many industries, including the pharmaceutical, biotech and medical device industries, manufacturing and device surfaces must be cleaned after use to remove potentially harmful contaminants. The sufficient cleaning of such surfaces is often critical and must be performed prior to resuming use of the surfaces for a new process. For example, in the pharmaceutical industry, if machinery is used to process a first product, it must be sufficiently cleaned before transitioning to use of the same machine for a second product so as to avoid cross contamination of the second product with the first product.
In order to insure the effectiveness of a cleaning process, the process applied to such surfaces must be verified to have been effective prior to releasing the surface for use on a new process or product. For example, federal regulations require inspection of manufacturing surfaces prior to returning those surfaces to use.
Inspection is typically performed through visual inspection by human operators. However, visual inspection is prone to variation and errors due to differences in lighting conditions, viewing angle and distance, eyesight and age of inspector, training of the operator, or lack thereof, and a wide variety of other variables. Further, visual inspection has not been qualified as a method. If an inspector approves a surface after inspection, the actual level of residue on the surface is not known at the time of inspection as the inspection process is not validated as to its accuracy, precision, or linearity or limits of detection. Further, there is no documentation that the visual inspection was actually performed other than by the signature of the operator.
Previous approaches to these problems typically relate to providing training to inspectors to better observe and evaluate residues on surfaces. This may be through training inspectors using “coupons” standards illustrating residue levels. However, none of these previous approaches have been demonstrated to be consistently accurate, precise, linear, or what their limits of detection are and they do not generate documented evidence that the visual inspection was actually performed.
Further, these previous approaches do not provide quantification of the residue amount. Although a visual “threshold” limit may be assumed from published literature, no calculated value or assumed value is provided by the inspection. Accordingly, existing processes are qualitative (Pass/Fail) and subjective instead of quantitative and objective, and therefore are not consistent and repeatable.